Thermal camera health monitoring

ABSTRACT

Methods and apparatus, including computer program products, for detecting a problem with a thermal camera. A current contrast value is determined for the thermal camera. It is determined whether the current contrast value deviates from a reference contrast value by more than a predetermined value. In response to determining that the current contrast value deviates from the reference contrast value by more than a predetermined value and for more than a predetermined period of time, an indication of a problem with the thermal camera is provided.

BACKGROUND

The present invention relates to thermal cameras, and more specificallyto automatically detecting various types of problems related to athermal camera.

Thermal cameras are used in a wide variety of monitoring situations.They are often preferable over monitoring cameras that operate in thevisible range of the electromagnetic spectrum, as the thermal camerasmay operate under essentially any light conditions, ranging from pitchdark to sunlight. They are also less sensitive to different lightconditions, such as shadows, backlight, darkness and even camouflagedobjects. Even in difficult weather conditions, such as smoke, haze, dustand light fog, thermal cameras generally have very good performance.Further, as thermal cameras do not need floodlights even in completedarkness, they also reduce light pollution and lower energy consumption.

Thermal cameras can detect very small differences in temperature, whichmakes it more difficult for a human to blend with the background.Therefore, thermal cameras are excellent at detecting humans obscured bycomplex backgrounds or hidden in deep shadows. In addition, many othertypes of objects also have a different temperature than the surroundingenvironment, making detection easy. For at least these reasons, thermalcameras can be used in a wide range of security applications, such asperimeter protection around industrial sites, airports and power plants.Their detection capabilities also make them a valuable tool, forexample, in search and rescue operations.

As an example, a live video from a thermal camera can inform a cameraoperator about a person walking among the cars in a parking lot longbefore a visual camera would detect the movement. When it comes toidentification, it is possible to use thermal cameras in situationswhere privacy is an issue, such as at schools.

Compared to visual cameras, thermal cameras can provide more reliabledetection and shape recognition by combining high image contrast withmotion detection. This results in fewer false alarms and reducesunnecessary responses and actions by personnel. The cameras also addthermal information to the image, making it possible to monitorprocesses and detect abnormal behavior when temperatures change, forexample, to find heat leaks in buildings or determine whether a car hasbeen driven within a recent period.

Generally, video captured by thermal cameras is not continuouslymonitored. Rather, only when an event occurs is the operator alerted andwill then determine what the problem may be and take an appropriateaction. This means that if a thermal camera is tampered with oraccidentally redirected, or if the thermal camera becomes dirty, thismay go unnoticed for quite some time and might result in varioussecurity and reliability issues. This is particularly relevant forsystems that include a large number, say a thousand or so, of monitoringcameras, where it may not be feasible or possible for a camera operatorto check the “health” of each camera with sufficient regularity. For atleast these reasons, there is a need for better methods for detectingmalfunction of a thermal camera.

SUMMARY

A first aspect of the teachings relate to a method, in a computersystem, for detecting a problem with a thermal camera. The methodincludes:

-   -   determining a current contrast value for the thermal camera;    -   determining whether the current contrast value deviates from a        reference contrast value by more than a predetermined value; and    -   in response to determining that the current contrast value        deviates from the reference contrast value by more than a        predetermined value and for more than a predetermined period of        time, providing an indication of a problem with the thermal        camera.

This provides a way of automatically detecting whether there is aproblem with the thermal camera, such as there being dirt on the lens, adeterioration of the image sensor or a mechanical shutter that is stuck,the camera having been tampered with, etc., and alerting a user aboutsuch a problem. This is particularly useful in large surveillance camerasystems where it may not be feasible to continuously monitor all camerasmanually.

According to one embodiment the problem can be one of: the thermalcamera having been tampered with, the thermal camera having beenredirected, and the lens of the thermal camera being affected in a waythat causes transmission loss. That is, a wide range of different typesof problem can be discovered using the techniques described herein.Again, while problems may be easy to detect manually in individualcameras, the risk of undetected camera problems may increase in largesystems that may contain hundreds or thousands of cameras, and thereforeit is important to have reliable automated methods for detecting cameramalfunction.

According to one embodiment, the reference contrast value and thecurrent contrast value can be determined using one of: a Sobelalgorithm, a Laplace algorithm, a Michelson contrast algorithm, and animage entropy algorithm. Different types of algorithms may prove more orless useful under certain circumstances, and may require differentcomputational resources, so being able to adapt the algorithm based onthe specific situation at hand can make the problem detection efficientand accurate.

According to one embodiment, the reference contrast value is based on aJohnson criterion pertaining to one or more of: detection, recognitionand identification of an object having a temperature that differs fromthe temperature of a homogenous background.

According to one embodiment, the reference contrast value is generatedthrough applying a machine learning process on measured contrast valuesover a period of time. This allows a time-varying reference contrastvalue to be used, rather than a fixed one, which may significantlyimprove the accuracy of the system.

According to one embodiment, the method can include: starting a timer inresponse to an earliest determination that the current contrast valuedeviates from the reference contrast value by more than thepredetermined value; at regular time intervals, repeating thedetermination of a current contrast value and the determination ofwhether the current contrast value deviates from the reference contrastvalue; and in response to detecting that the current contrast valuesremain deviant from the reference contrast value by more than thepredetermined value and for more than a predetermined period since thetimer was started, providing the indication of a problem related to thethermal camera. That is, a timer can be started and reset based on thedetected contrast values and how they relate to the predeterminedcontrast value, and a predetermined period can be set to define at whatpoint an alert should be generated. Using timers in combination withcontrast measurements is an easy and computationally low-cost way ofdetermining whether a problem has occurred, or whether there may justhave been a temporary issue (e.g., a bird flying past the camera ordebris temporarily covering the camera lens) at the time a particularimage was taken. There may also be weather-related events, of course,such as dense fog or significant precipitation, that causes the contrastvalue to drop below a certain threshold without there being any problemwith the camera.

According to one embodiment, the regular time intervals range fromapproximately one to three days. Typically, degradations of thermalcameras do not occur very rapidly, so in general, taking measurementswith this type of frequency is sufficient. However, again, this isspecific to the particular circumstances at hand. For instance, if thecamera is accessible to a potential vandal or if it is mounted in a spotwith many birds, it may be useful to set a shorter time interval than ifthe camera is out of reach and well sheltered.

According to a second aspect, a system for detecting a problem with athermal camera includes a memory and a processor. The memory containsinstructions that when executed by the processor causes the processor toperform a method that includes:

-   -   determining a current contrast value for the thermal camera;    -   determining whether the current contrast value deviates from a        reference contrast value by more than a predetermined value; and    -   in response to determining that the current contrast value        deviates from the reference contrast value by more than a        predetermined value and for more than a predetermined period of        time, providing an indication of a problem with the thermal        camera.

The system advantages correspond to those of the method and may bevaried similarly.

According to a third aspect, a thermal camera includes a system asdescribed above, for detecting a problem with the thermal camera. Theadvantages of the camera correspond to those of the system and may bevaried similarly.

According to a fourth aspect, a computer program for detecting a problemwith a thermal camera contains instructions corresponding to the stepsof:

-   -   determining a current contrast value for the thermal camera;    -   determining whether the current contrast value deviates from a        reference contrast value by more than a predetermined value; and    -   in response to determining that the current contrast value        deviates from the reference contrast value by more than a        predetermined value and for more than a predetermined period of        time, providing an indication of a problem with the thermal        camera.

The computer program involves advantages corresponding to those of themethod and may be varied similarly.

The details of one or more embodiments are set forth in the accompanyingdrawings and the description below. Other features and advantages willbe apparent from the description and drawings, and from the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flowchart depicting a process for detecting a problem with athermal camera, in accordance with one embodiment.

FIG. 2 is a schematic diagram showing time varying predeterminedcontrast values and actual contrast value measurements, in accordancewith one embodiment.

Like reference symbols in the various drawings indicate like elements.

DETAILED DESCRIPTION

As was described above, one goal with the various embodiments is to beable to automatically detect a problem with a thermal camera. At ageneral level, the various embodiments work as follows.

The contrast value in an image (i.e., the degree of difference betweenthe highest and lowest intensity parts of an image) captured by thethermal camera is measured over time and is compared to a contrast valuethreshold that represents a correctly installed and correctlyfunctioning thermal camera. If the contrast values of the capturedimages fall below the contrast value threshold and remain below thecontrast value threshold for a predetermined time, this might indicatethat the thermal camera has been tampered with or suffered some sort ofdegradation, and an operator may be alerted to further investigate thepossible problem. Various embodiments will now be described in greaterdetail by way of example and with reference to the drawings. First,however, a brief overview of thermal cameras will be presented.

A conventional network camera operating in the visible range of theelectromagnetic spectrum and a thermal network camera are similar inmany aspects, such as compression and the networking features,availability of different form factors for use in different environmentsand situations, etc. However, two things differ substantially: the lensand the sensor.

Because regular glass blocks thermal radiation, regular glass-basedoptics and lenses cannot be used in thermal cameras. Currently,germanium is the most commonly used material for thermal camera optics.Germanium, which is an expensive metalloid that is chemically similar totin and silicon, blocks visible light while letting through the IRlight. There are also alternatives to using pure germanium. For example,some lenses are made of a germanium-based material called chalcogenideglass, which allows a wider spectrum of IR light to pass through.

The sensor in a thermal camera is an array of thousands of detectorsthat are sensitive to thermal infrared (IR) radiation. The detectorsused for thermal imaging can be broadly divided into two types: cooledand uncooled IR sensors. Uncooled IR image sensors are smaller and builtwith fewer moving parts, which makes them less expensive than theircooled counterparts. Cameras with cooled sensors generally need to beserviced, and also have the cooling medium refilled every 8,000-10,000hours. Most commercially available thermal cameras use uncooled IRsensors, and therefore the description herein will refer to suchsensors. However, it should be noted that the techniques in accordancewith the various embodiments herein can also be applied to cameras thathave cooled sensors, and that the claims should not be construed asbeing limited only to thermal cameras with uncooled sensors.

Uncooled sensors typically operate in the Long-wave Infrared (LWIR)band, at about 8-15 micrometers wavelength, and can be based on avariety of materials that all offer unique benefits. One common designis based on microbolometer technology, which are well known to thosehaving ordinary skill in the art. Microbolometers generally make up anarray of pixels, each constructed from a microbolometer includingthermo-sensing material whose electrical resistivity changes as itabsorbs incident IR radiation. The IR-absorbing material is connected toa read-out circuit by means of electrodes and a reflector is arrangedinside the IR-absorbing material for reflecting back IR radiationpassing through the absorbing material. In order to reduce the influenceof convection on the heat absorbing properties of the pixels, themicrobolometer is encapsulated in vacuum. A getter material may bedeposited in the microbolometer for reacting with or adsorbing gasmolecules released inside the microbolometer, thereby extending thelongevity of the vacuum. IR radiation incident on the microbolometerchanges the resistivity of the IR-absorbing material, and the change istransferred to the read-out circuit for processing. The change inresistivity is translated into a temperature of the part of the capturedscene from which the IR radiation originated.

Resolutions are generally lower for thermal cameras than forconventional network cameras. This is mostly due to the more expensivesensor technology involved in thermal imaging. The pixels are larger,which affects the sensor size and the cost of materials and production.Currently, typical resolutions for thermal cameras range from 160×120 tohigh resolutions of 640×480 (VGA), though even higher and lowerresolutions are available.

The resolution of the thermal camera is also connected to its ability todetect an object. The resolution required to detect an object is statedin pixels and determined by means of the so-called “Johnson's criteria.”These criteria provide a 50% probability of an observer distinguishingan object at the specified level, and for a thermal sensor, thetemperature difference between the object and its background needs to beat least 2° C. (3.6° F.). In one implementation, the levels of Johnson'scriteria used for thermal network cameras are as follows:

-   -   At least 1.5 pixels are needed for detection (i.e., the observer        can see that an object is present).    -   At least 6 pixels are needed for recognition (i.e., the observer        can distinguish the object, for example, a person in front of a        fence).    -   At least 12 pixels are needed for identification (i.e., the        observer can distinguish an object and object characteristics,        for example, a person holding a crowbar in his hand).

Johnson's criteria were developed under the assumption that visibleinformation is processed by a human observer. If information is insteadprocessed by an application algorithm, there will be specificrequirements about the number of pixels needed on the target forreliable operation. All video analytics software algorithms need to workwith a certain number of pixels, but the exact number of pixels mayvary. Even if a human observer is able to detect the object, theapplication algorithm often needs a larger number of pixels at a givendetection range to work properly.

An analogous type of criteria can be used to determine a referencecontrast for an image, against which measured contrast values can becompared, as will now be discussed in greater detail with reference toFIG. 1, which shows a flowchart of a method 100 for detecting a problemwith a thermal camera, in accordance with one embodiment. As can be seenin FIG. 1, the method 100 starts by determining a contrast value for acurrent image that is captured by the thermal camera, step 102. Thecontrast value can be determined in a number of ways that are familiarto those of ordinary skill in the art. A few examples will be given herealong with their respective advantages and drawbacks. It is to beunderstood that various methods may be better or worse to use, based onthe specific circumstances at hand, and that what specific algorithm touse under what conditions is a choice to be made by the skilled artisan.

One method for determining contrast is to use Michelson Contrast, whichis a global measure of the contrast in an image. The Michelson Contrastfunction does not catch any features like sharp edges in the image andinstead operates only on the minimum and the maximum pixel intensity inthe image. The larger difference between the minimum and maximum pixelintensities in the image, the greater output of the function.

Another method for determining contrast is to use RMS (Root Mean Square)contrast, which uses the root-mean-square of the image as the definitionfor contrast. The RMS formula takes into account not only the pixelintensities, but also the width and height of the image. Thismeasurement is also global, but takes more pixels into account than justthe maximum and the minimum pixel intensity values in the image. A highintensity variance among the pixels contributes to higher contrast.

Yet another method for determining contrast is to use a Sobel filter.The Sobel filter is a measurement which is typically used as an edgedetection algorithm rather than a contrast measurement. It works bysweeping two separate convolution kernels over the image, one for edgedetection along the x-axis and the other for edge detection along they-axis. Since the Sobel operator is good at detecting sharp edges in theimage, it can be seen as a measure of contrast as high contrast is oftenperceived when an image has sharp edges. This is useful to find imagesamples where the lens is unfocused because there are no sharp edges inthe image.

The output of the Sobel algorithm is an entire image, which means thatthe Sobel filtering must be followed by some kind of mapping of theimage down to a single value that subsequently can be used forcomparison purposes. This can be done in several ways. Onestraightforward way to measure the contrast is to pick the maximum valuein the output Sobel image. This is cheap in computation; however, asingle sharp edge in the image will be sufficient to enough to classifythe image as having high contrast, which may not always be desirable.Another way is to make a measurement which takes all pixels intoaccount, and measure the contrast based on how much the pixels in theSobel image deviate from zero. Yet another way to reduce the Sobel to asingle contrast measure value is to use the mean of the output image.This takes all pixels into account and allows all edges, both in numberand sharpness, to contribute to the output value. It should be notedthat these are merely a few representative techniques, and there aremany other variations that fall within the capabilities of those havingordinary skill in the art.

After determining the contrast, a determination is made as to whetherthe contrast value deviates from a reference contrast value by more thana predetermined contrast value, step 104. In some implementations, thepredetermined contrast value can be a fixed value that is determinedbased on the Johnson criteria, as discussed above. That is, there can beone predetermined contrast value for detection, there can be another onefor recognition and yet another for identification, and based on theparticular situation and a particular predetermined contrast value canbe used.

In some implementations, the predetermined contrast value may not bedetermined using the Johnson criteria. Instead, it may be determinedexperimentally during setup of the camera, for example, by measuringpredetermined contrast values that are required for detection,recognition and identification, respectively, of objects or peopleagainst a homogeneous background, and using these measured values aspredetermined contrast values.

In yet other implementations, the predetermined contrast value can besimulated by defocusing or otherwise degrading a monitored scene untilthe scene is deemed visually by an operator to be too “fuzzy” or to havetoo low quality, and then base the predetermined contrast values basedon such a simulation.

It should be noted that the predetermined contrast value can also varywith time, for example, based on the time of day, the time of year,etc., and based on the weather. This time variable value can bedetermined, for example, by measuring contrast values over a period oftime and using a machine learning algorithm to define what would be a“normal” contrast value for a given set of circumstances, and then usethat “normal value” as the contrast reference value. FIG. 2 showsschematically how actual contrast measurements (top curve) vary overtime. These measurements can be interpolated to a curve (middle curve)that describes the expected variation over time. Finally, a varyingpredetermined threshold value can be set (lower, dashed curve), forexample an 80% of the values of the interpolated curve, that can be usedas the predetermined threshold value at any given time.

If the measured contrast value falls within the acceptable range, atimer is reset, step 106, and the process goes back to step 102 andcontinues as explained above with measuring a contrast value for anotherimage. The frequency by which the contrast measurements occurs can vary,but in some implementations a contrast measurement is typically madeapproximately every 10 minutes.

However, if the measured contrast value falls outside the acceptablerange, a timer is read, step 108, and the timer value is then examinedto see if the timer has expired in step 110. If the timer has notexpired, the process returns to step 102 as described above. What thiseffectively means is that the first time the contrast value of ameasured image goes below the predetermined contrast value, the time atwhich this occurs is noted. Then as contrast values are determined fornew images and these contrast values (or at least a significant majorityof them) keep lying below the threshold value the method keeps track ofhow long this has been going on. When a certain amount of time haspassed (i.e., the timer has expired) and the contrast values still lieunder the threshold value, an alert is generated, step 112, which endsthe process. The expiration time for the timer can be determined by auser, but is typically in the range of one to three days for a camerathat is placed in an outdoor environment, and typically shorter for acamera that is placed in an indoor environment. However, it should benoted that these values are highly dependent on the context, and will inmost situations have to be adjusted by an operator of the camera to fitthe particular situation at hand.

The alert generated in step 112, can for example be an alert to a cameraoperator that the thermal camera is suffering some kind of problem andneeds to be examined manually, or could be an alert to a maintenanceteam to run some kind of test sequence on the camera, or could be aninstruction to switch over to a different camera covering the same sceneuntil the problem has been resolved. Many variations can be envisionedby those having ordinary skill in the art. The alert may be presented tothe operator in any of several possible ways, such as through an onscreen message in a video management system, a text message to theoperator's mobile phone, or an audio message via a speaker in a controlcenter.

As will be appreciated by one skilled in the art, aspects may beembodied as a system, method or computer program product. Accordingly,aspects may take the form of an entirely hardware embodiment, anentirely software embodiment (including firmware, resident software,micro-code, etc.) or an embodiment combining software and hardwareaspects that may all generally be referred to herein as a “circuit,”“module” or “system.” Furthermore, aspects of the present teachings maytake the form of a computer program product embodied in one or morecomputer readable medium(s) having computer readable program codeembodied thereon.

Any combination of one or more computer readable medium(s) may beutilized. The computer readable medium may be a computer readable signalmedium or a computer readable storage medium. A computer readablestorage medium may be, for example, but not limited to, an electronic,magnetic, optical, electromagnetic, infrared, or semiconductor system,apparatus, or device, or any suitable combination of the foregoing. Morespecific examples (a non-exhaustive list) of the computer readablestorage medium would include the following: an electrical connectionhaving one or more wires, a portable computer diskette, a hard disk, arandom access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or Flash memory), an optical fiber,a portable compact disc read-only memory (CD-ROM), an optical storagedevice, a magnetic storage device, or any suitable combination of theforegoing. In the context of this document, a computer readable storagemedium may be any tangible medium that can contain, or store a programfor use by or in connection with an instruction execution system,apparatus, or device.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer medium that is not acomputer readable storage medium and that can communicate, propagate, ortransport a program for use by or in connection with an instructionexecution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing. Computer program code for carrying out operations foraspects of the present embodiments may be written in any combination ofone or more programming languages, including an object orientedprogramming language such as Java, Smalltalk, C++ or the like andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The program codemay execute entirely on the user's computer, partly on the user'scomputer, as a stand-alone software package, partly on the user'scomputer and partly on a remote computer or entirely on the remotecomputer or server. In the latter scenario, the remote computer may beconnected to the user's computer through any type of network, includinga local area network (LAN) or a wide area network (WAN), or theconnection may be made to an external computer (for example, through theInternet using an Internet Service Provider).

Aspects of the present teachings are described with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems) and computer program products according to embodiments. Eachblock of the flowchart illustrations and/or block diagrams, andcombinations of blocks in the flowchart illustrations and/or blockdiagrams, can be implemented by computer program instructions. Thesecomputer program instructions may be provided to a processor of ageneral purpose computer, special purpose computer, or otherprogrammable data processing apparatus to produce a machine, such thatthe instructions, which execute via the processor of the computer orother programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

These computer program instructions may also be stored in a computerreadable medium that can direct a computer, other programmable dataprocessing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablemedium produce an article of manufacture including instructions whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments set forth herein. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks may occur out of theorder noted in the Figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The descriptions of the various embodiments have been presented forpurposes of illustration, but are not intended to be exhaustive orlimited to the embodiments disclosed. Many modifications and variationswill be apparent to those of ordinary skill in the art without departingfrom the scope and spirit of the described embodiments. Thus, many othervariations that fall within the scope of the claims can be envisioned bythose having ordinary skill in the art.

The terminology used herein was chosen to best explain the principles ofthe embodiments, the practical application or technical improvement overtechnologies found in the marketplace, or to enable others of ordinaryskill in the art to understand the embodiments disclosed herein.

What is claimed is:
 1. A method for detecting a problem with a thermalcamera, comprising: determining a current contrast value for the thermalcamera; determining whether the current contrast value deviates from areference contrast value by more than a predetermined value; in responseto determining that the current contrast value deviates from thereference contrast value by more than a predetermined value, starting atimer; and in response to determining that the current contrast valuedeviates from the reference contrast value by more than a predeterminedvalue and for more than a predetermined period of time since the timerwas started, providing an indication of a problem with the thermalcamera.
 2. The method of claim 1, wherein the problem is one of: thethermal camera having been tampered with, the thermal camera having beenredirected, and the lens of the thermal camera being affected in a waythat causes transmission loss.
 3. The method of claim 1, wherein thereference contrast value and the current contrast value are determinedusing one of: a contrast value representative of a Sobel image obtainedby applying a Sobel algorithm to an image captured by the thermalcamera, a Michelson contrast algorithm applied to the image captured bythe thermal camera, and an image entropy algorithm applied to the imagecaptured by the thermal camera.
 4. The method of claim 1, wherein thepredetermined value is based on a Johnson criterion pertaining to one ormore of: detection, recognition and identification of an object having atemperature that differs from the temperature of a homogenous backgroundby at least 2° C., and wherein at least 1.5 pixels are used fordetection of the object, at least 6 pixels are used for recognition ofthe object and at least 12 pixels are used for identification of theobject.
 5. The method of claim 1, wherein the reference contrast valueis generated through applying a machine learning process on measuredcontrast values over a period of time.
 6. The method of claim 1, whereinproviding an indication of a problem further comprises: starting a timerin response to an earliest determination that the current contrast valuedeviates from the reference contrast value by more than thepredetermined value; at regular time intervals, repeating thedetermination of a current contrast value and the determination ofwhether the current contrast value deviates from the reference contrastvalue; and in response to detecting that the current contrast valuesremain deviant from the reference contrast value by more than thepredetermined value and for more than a predetermined period since thetimer was started, providing the indication of a problem related to thethermal camera.
 7. The method of claim 6, wherein the regular timeintervals range from approximately one to three days.
 8. A system fordetecting a problem with a thermal camera, comprising: a memory; and aprocessor, wherein the memory contains instructions that when executedby the processor causes the processor to perform a method that includes:determining a current contrast value for the thermal camera; determiningwhether the current contrast value deviates from a reference contrastvalue by more than a predetermined value; in response to determiningthat the current contrast value deviates from the reference contrastvalue by more than a predetermined value, starting a timer; and inresponse to determining that the current contrast value deviates fromthe reference contrast value by more than a predetermined value and formore than a predetermined period of time since the timer was started,providing an indication of a problem with the thermal camera.
 9. Athermal camera including a system as described in claim
 8. 10. Anon-transitory computer readable storage medium having programinstructions embodied therewith, the program instructions beingexecutable by a processor to perform a method for detecting a problemwith a thermal camera, the comprising method comprising: determining acurrent contrast value for the thermal camera; determining whether thecurrent contrast value deviates from a reference contrast value by morethan a predetermined value; in response to determining that the currentcontrast value deviates from the reference contrast value by more than apredetermined value, starting a timer; and in response to determiningthat the current contrast value deviates from the reference contrastvalue by more than a predetermined value and for more than apredetermined period of time since the timer was started, providing anindication of a problem with the thermal camera.